Environmental Warning System Based on the DPSIR Model: a Practical and Concise Method for Environmental Assessment

sustainability

Article Environmental Warning System Based on the DPSIR Model: A Practical and Concise Method for Environmental Assessment

Wenqi Wang 1, Yuhong Sun 2,* and Jing Wu 1,* 1 College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; [email protected] 2 Yunnan Provincial Appraisal Center for Environmental Engineering, Kunming 650032, China * Correspondence: [email protected] (Y.S.); [email protected] (J.W.)

Received: 7 May 2018; Accepted: 17 May 2018; Published: 25 May 2018

Abstract: Though we are in urgent need of environmental warnings to slow environmental deterioration, currently, there is no internationally concise method for environmental warnings. In addition, the existing approaches do not combine the three aspects of ecology, resources, and environment. At the same time, the three elements of the environment (air, water, and soil) are separated in most environmental warning systems. Thus, the method this paper gives is an innovative attempt and aims to make environmental assessment more practical. This paper establishes the index system of an environmental early warning based on the Driving–Pressure–State–Inﬂuence–Response (DPSIR) model. The Analytic Hierarchy Process (AHP) method was used to determine the weights. Next, single and integrated index methods further assess the environmental warning state, in which the weighted summation method is used to summarize the data and results. The case of Tianjin is used to conﬁrm the applicability of this method. In conclusion, the method in this paper is more well-behaved and, therefore, more suitable to assist cities in their environmental assessment.

Keywords: DPSIR; environmental warning; environmental impact assessment; index system

1. Introduction With the development of society, although the economic development met the growing material needs of people, it also brought a great negative externality to the environment, such as the rise of the particulate matter that has an aerodynamic diameter of 2.5 microns or smaller (PM2.5), the eruption of cyanobacteria, the emergence of black and smelly rivers, and the heavy metal pollution of the soil. These environmental deterioration problems have attracted widespread attention and urgently call for more effective environmental governance policies to reduce the environmental pollution. Only by doing this can we achieve a win–win situation for economic development and environmental protection. Furthermore, environmental warning, as an effective policy, can speed up the construction of ecological civilization and ecological protection. Early warning, that is, the provision of timely and effective information through identiﬁed institutions, allows individuals exposed to a hazard to take action to avoid or reduce their risk and prepare an effective response [1]. Similarly, timely environmental warnings can predict the degradation and deterioration of environmental quality caused by industrial development activities [2]. They have a pioneering, predictive, and advanced function, as well as a vigilance effect on the evolutionary trend, direction, speed, and consequences [3]. Therefore, carrying out environmental early warning is an important measure to implement decision-making arrangements and promote the formation of a green development mode. It is also a key point for promoting environmental impact assessment (EIA) and strategic environmental assessment (SEA) and improving land space governance system.

Sustainability 2018, 10, 1728; doi:10.3390/su10061728 www.mdpi.com/journal/sustainability Sustainability 2018, 10, 1728 2 of 20

In previous studies, environmental warnings were divided into environmental carrying capacity warning, environmental risk warning, and environmental ecology warning. Environmental carrying capacity warning is still in its infancy. The study of environmental carrying capacity evolved from the study of the land carrying capacity in ecology and the concept of environmental capacity [4]. In the past years, Scholars [5–9] introduced early warning systems for marine, livestock and poultry breeding, and river carrying capacity. At this stage, many carrying capacity warning methods are beginning to emerge, such as the Long-Term Ecosystem Research and Monitoring Method (LTERM) proposed by Parr. In the last five years, early warning systems for marine carrying capacity have developed tremendously, such as for Xiamen Bay [10] and Qingdao [11]. Moreover, the water carrying capacity warning has entered a period of rapid growth [12–17], including in Yogyakarta Urban Area (YUA), the Liao River Basin, the Haihe, Yangtze River, and Kunming. It is worth mentioning that more and more scholars turn from single carrying capacity warning to the comprehensive carrying capacity warning, such as case studies of Henan Province [18] and the Beijing–Tianjin–Hebei region [19]. At the same time, many methods have been adopted to calculate carrying capacity in early warning systems such as index evaluation, state space, the ecological footprint, the system dynamics model, single factor analysis, fuzzy comprehensive evaluation, and studio analysis [20]. With the increasing importance of accidental pollution incidents control, environmental risk warning has gained widespread attention in developed countries since the 1970s. In 1989, the United Nations Environment Program proposed the Awareness and Preparedness for Emergencies at Local Level (APELL) Program [21]. As early as the last century, the Danube River Basin Water Pollution Warning System was developed jointly by Germany and Austria, and the German water pollution early warning system was developed in the Rhine River Basin [22]. Today, through thirty years of development, the environmental risk warning system has already made great progress in a range of applications, which usually focused on the water quality emergency risk and catastrophes. Accordingly, with the development of the water quality emergency risk, a mobile environment decision support system (MEWSUB) [23–25] has been built and, for catastrophe warning, the United Nations’ International Strategy for Disaster Reduction (ISDR) suggested that early warning systems possessed the following four mechanisms [26,27]: risk knowledge, monitoring and warning service, dissemination and communication, and response capability. In addition, since 2013, the Ministry of Environmental Protection issued a notice that, to improve air pollution prevention and mitigate the impact of pollution, all localities should strengthen the air early warning under the heavily polluted weather. Therefore, Chinese scholars [28–30] used forecasting models and fuzzy evaluation to make early warning systems in Taiyuan, Harbin, Chongqing, Chengdu, and Hangzhou. Since the development of environmental ecology warning, relevant theories have been constantly improved and technical methods have been updated, and there were both single warnings and comprehensive warnings in ecological warning. In terms of single warnings, there were flood warning systems, pasture warning systems, and soil warning systems. In terms of comprehensive warning, the United Nations Development Program established the Division of Early Warning and Assessment (DEWA) system. In addition to the establishment of national institutions, scholars also concentrated on comprehensive warnings on soil, cultivated land, and agriculture [31–34]. In China, the research on environmental ecological warning has been given more attention by academics. At the provincial and municipal scales, scholars used gray system theory and BP artificial neural networks to study the influence of factors in Inner Mongolia Autonomous Region, Suzhou, Kaifeng, Huangshan, Zhengzhou, and Shanghai to propose measures for sustainable development [35,36]. At the environmental ecology warning river basins scale, scholars used available environmental ecology warning data to study the typical river basin in the Yellow River Delta, Dongting Lake, Chaohu Lake, Tumen River, Tuojiang River, Wujiang River, and Heihe River [37–39]. In July 2016, the Ministry of Environmental Protection published the “Implementation Plan for the Reform of Environmental Impact Assessment in the 13th Five-Year Plan period” [40], calling for Sustainability 2018, 10, 1728 3 of 20 the establishment of environment early warning systems based on big data, formulating early warning indicator systems, models, and technical methods. To meet new requirements, we have to reconstruct the index system of environmental warnings. Combining the three major environmental factors of water, atmosphere, and soil, and considering the related requirements in China’s strategic environmental assessment (SEA), this study innovatively divided environmental early warning into three aspects. The first one is environmental ecology warning, which can reflect the current situation and trend of ecology overall. The second one is the environmental quality warning, which represents not only a better or worse environment, but also the bottom line of the environmental elements. Environmental quality warning in this study is similar to the environmental carrying capacity warning, but it is more accurate than the carrying capacity warning in reflecting the environmental deterioration trend. Briefly, environmental quality warning, in this study, is that which starts an early warning before it reaches its bearing capacity. The last one is environmental resources warning. In this research, we mainly study water resources warnings, which can delimit the upper limit of water resources utilization. This paper is divided into six sections. Section1 is the research background and status quo at home and abroad. Section2 introduces the research methods, including the model selection, construction of index system, weight determination, index grading and two index evaluation methods. In Section3, a case study of Tianjin is used to verify the rationality of the methods. The results show that the ecological environment in Tianjin is facing more pressure and the air, water, soil, and ecosystems are in poor condition. To promote the sustainable and coordinated development of the environment and economy in Tianjin, ecological corridors and biodiversity conservation networks should be established. Finally, some significant discussion points and conclusions are listed.

2. Methods

2.1. Model Selection At present, most of the studies on index systems adopt the Driving–Pressure–State–Influence– Response (DPSIR) model. In 1979, Canada pioneered the State–Response (S–R) model. Later, the S–R model evolved into the Pressure–State–Response (PSR) model. Afterwards, the PSR model evolved into DPSIR model that included human activities, stress, environmental state, impacts on ecosystems, human health, and political responses [41,42]. The practical application over the years has shown that the DPSIR model has the advantages of comprehensiveness, operability, systematization, and integrity. First, the DPSIR model covers important elements of economy, society, resources, and environment, which can clearly and simply reflect the relationship between the environment and other factors, thus it can provide a scientific theoretical basis for policymakers. Secondly, it not only indicates the influence of society, economic development, and human behavior on the consumption of resources and ecological environment, but also shows the feedback of human behavior and its final lead to the state of resources and environment, which makes the whole system a cycle. Thirdly, it provides a basic framework for the construction of the environmental index system and is suitable for early warnings and the assessment of the environment. Lastly, its evaluation process is relatively easy to operate and use, which brings convenience to scientific researchers. Therefore, this study used the DPSIR model as a research method.

2.2. Construction of the Index System Based on the DPSIR model, reference was made to the “National Environmental Protection Plan for the Thirteenth Five-year” [43], “Opinions on Implementing a Strict Water Resources Management System” [44], ”Opinions on the Delineation and Strict Adherence to the Control Line of Ecological Protection” [45], and “the Technical Guide for the Delimitation of the Control Line of Ecological Protection” [46]. The index system of environmental warnings was analyzed layer by layer. Taking into Sustainability 2018, 10, x FOR PEER REVIEW 4 of 19

SustainabilityManagement2018 S, ystem”10, 1728 [44], ”Opinions on the Delineation and Strict Adherence to the Control Line4 of of 20 Ecological Protection” [45], and “the Technical Guide for the Delimitation of the Control Line of Ecological Protection” [46]. The index system of environmental warnings was analyzed layer by accountlayer. Taking the comprehensiveness, into account the dynamic comprehensiveness, continuity, operability, dynamic and continuity, the qualitative operability, and quantitative and the combinationqualitative and of indicators,quantitative the combination index system of wasindicators, established. the index system was established. The driving driving force (D)(D) isis usedused toto expressexpress thethe humanhuman socialsocial andand economiceconomic activities.activities. In general, population growth and demand development are the most fundamental driving forces. Therefore, in this this study, study, thethe driving driving force force indicators indicators mainly reflectedreflected the populationpopulation and economic level. level. Considering that PopulationPopulation density and GDP cannotcannot accurately measure population and economic level, we we used used the the correlation correlation coefficient coefficient to modify to modify indicators. indicators. Thus, Thus, Driving Driving force (D) force in this (D) research in this includesresearch theincludes population the population concentration concentration degree and degree the economic and the economic development development level. level. Pressure (P) exerts directly to the environment under the action of Driving force (D). Similar to the Driving force (D), Pressure (P) isis the externalexternal force acting on the development and change of thethe environment. However, However, thethe Driving Driving force force (D) (D) exerts exerts the theeffect effect on the on environmental the environmental implicitly implicitly while Pressurewhile Pressure (P) does (P) so does explicitly. so explicitly. Additionally, Additionally, Pressure Pressure (P) usually (P) usually reflects reflects the environmental the environmental impact ofimpact human of activities,human activities, waste discharge, waste discharge, and resource and resource consumption. consumption. Therefore, Therefore, in this index in this system, index thesystem, pressure the pressur indicatorse indicators include theinclude Reduction the Reduction of the construction of the construction land area land per area RMB per 10,000 RMB of 10,000 GDP, industrialof GDP, industrial exhaust emissions exhaust per emissions capita, sewageper capita, discharge sewage per discharge unit area, per the fertilizer unit area, utilization the fertilizer rate, theutilization water consumption rate, the water per consumption 10,000 Yuan GDP,per 10,000 and the Yuan water GDP, consumption and the water per 10,000consumption Yuan of per industrial 10,000 addedYuan of value. industrial added value. StateState (S) directly reflectsreflects the state of environment under the current pressure, which is usually indicated by the indicators indicators related to to the the efficiency efficiency and and compliance compliance rate. rate. Impact Impact (I) (I) is caused by human activitiesactivities that bringsbrings pressure on the environment and causescauses changes in the environmentenvironment and human health. Therefore, the index system includes the ecological redline rate, cultivated land safety index, eco-environmentaleco-environmental quality index, percentage of days per year with good air quality in cities, severe air pollution rate, centralized drinking water sources quality compliance rate, water functional area area compliance compliance rate, rate, cultivated cultivated land land soil soil quality quality compliance compliance rate, rate, contaminated contaminated land landsafe safeutilization utilization rate, rate, water water resources resources per per capita, capita, water water supply supply in in ecological ecological environment, environment, and and the groundwater over-exploitationover-exploitation rate.rate. Response (R) is the measures taken by individuals,individuals, social groups, or governments to prevent and control control the the ecological ecological environment environment damage damage and andpollution polluti oron improve or improve the environmental the environmental quality andquality adapt and to adapt new environmentalto new environmental changes, changes, which include which theinclud foreste the cover forest rate, cover soil rate, erosion soil erosion control rate,control environmental rate, environmental pollution pollution loss rate, loss effective rate, effective utilization utilization coefficient coefficient of farmland of farmland irrigation irrig water,ation sewagewater, sewage centralized centra treatmentlized treatment rate, rate, recycled recycled water water utilization utilization rate rate (six (sixquantitative quantitative indicators), the environmentalenvironmental management management system system soundness, soundness, and and the the environmental environmental risk risk system system perfection perfection (two qualitative(two qualitative indicators). indicators). The calculation method of each indicatorindicator isis listedlisted inin AppendixAppendixA A.. The The overall overall framework framework andand specificspecific indicators of the environment warningwarning indexindex systemsystem areare shownshown inin FigureFigure1 1 and and Table Table1. 1.

Figure 1. The environmental warning index system framework. Figure 1. The environmental warning index system framework. Sustainability 2018, 10, 1728 5 of 20

Table 1. The environmental early warning index system.

Ecological Environmental Quality DPSIR Water Resources Protection Air Water Soil D Population concentration degree, Economic development level Water consumption per RMB 10,000 of Reduction of Industrial Sewage GDP, construction land exhaust Fertilizer utilization P discharge per water consumption area per RMB emissions per rate unit area per RMB 10,000 of 10,000 of GDP capita industrial added value Percentage of days per year Centralized Water resources per Ecological redline with good air drinking water Cultivated land soil capita, water supply rate, quality in cities, sources quality quality compliance in ecological cultivated land S and I percentage of compliance rate, contaminated environment, safety index, days per year rate, water land safe utilization groundwater eco-environmental with severe air functional area rate over-exploitation quality index pollution in compliance rate rate cities Effective utilization coefﬁcient of Forest coverage Environmental management system soundness, farmland irrigation R rate, soil erosion environmental risk system perfection, water, sewage control rate environmental pollution loss rate centralized treatment rate, recycled water utilization rate

2.3. Weight Determination There are many ways to determine the weight of indicators, such as the Analytic Hierarchy Process (AHP), Expert consultation, Fuzzy comprehensive evaluation, Principal component analysis, Sequence synthesis, and Coordination evaluation. Analytic Hierarchy Process (AHP) is not only widely used in different fields such as the environment, society, and economy but also developed in theory [47]. It is also applicable to the index system with fewer indicators, which is practical. Therefore, in this research, AHP was used to weight the indicators of the criterion levels. The specific method is as follows: first, construct the judgment comparison matrix, compare the importance of two given factors, and use the –9 scale system proposed by Saaty to determine the value in the judgment matrix. Secondly, use SUM in Excel to calculate the largest eigenvalue (λmax) and its corresponding eigenvector, normalize each column of the judgment matrix to obtain the corresponding weight and calculate the arithmetic mean of each column vector as the final weight, that is, the sorted importance of each evaluation index. Finally, we test the matrix consistency.

Consistency Index (CI) = (λmax − n)/(n − 1) (1)

Consistency Rate (CR) = Consistency Index (CI)/Random Index (RI) (2)

The random consistency index RI is shown in Table2. After examination, the CR of the matrix set in this research was less than 0.1, which is considered to be in good agreement.

Table 2. The random consistency index (RI).

Matrix Order 1 2 3 4 5 6 7 8 9 10 RI 0 0 0.52 0.89 1.12 1.26 1.36 1.41 1.46 1.49 Sustainability 2018, 10, 1728 6 of 20

2.4. Index Grading Index grading of this study was mainly based on existing environmental standards, relevant national guidelines, management methods, eco-villages, and eco-provincial construction indicators, as well as existing research literature and provincial data. Specifically, the grading sources of specific indicators were as follows: (1) “Resources–Environment–Economy Compound System Diagnostic Early Warning Method and Application” [48]; (2) “Practice and Exploration on Resources and Environmental Carrying Capacity Monitoring and Early Warning of the Sichuan Province” [49]; (3) ”Guiding Opinions on the Implementation of Decreasing Construction Land Area Per Gross Domestic Product in the 13th Five-Year” [50]; (4) “Temporal and Spatial Distribution of Cropland-Population-Grain System and Pressure Index on the Cropland in the Jinghe Watershed” [51]; (5) “Eco-Environment Security Assessment Study for the Binhai New Area, Tianjin, Based on the DPSIR Model” [52]; (6) “Soil Erosion Prevention and Control Standards for Construction Projects” (GB50434-2008) [53]; (7) “Indicators of National Ecological Civilization Demonstration Counties and Cities (Trial Implementation)” [54]; (8) “Action Plan for Zero Growth of Fertilizer Consumption by 2020” [55]; (9) “National Environmental Protection Plan for the Thirteenth Five-Year” [43]; (10) “Action Plan for the Prevention and Control of Soil Pollution” [56]; (11) “Study on Urban Eco-Environmental Water Requirements: Theory and Method” [57]; (12) “Guidelines for the Evaluation of Groundwater Overdraft Area (GB/T 34968-2017)” [58]; (13) “Green is Gold: The Strategy and Actions of China’s Ecological Civilization” [59]; and (14) “Opinions on Implementing Strict Water Resources Management System” [44]. Afterwards, referring to the provinces environmental statement, based on the five grades determined, the index grading of all indicators were ascertained. The warning weight setting and index grading are shown in Tables3–7.

Table 3. The environmental ecology warning weight setting and index grading.

Standard Index Layer Attribute Weight Red Orange Yellow Green Blue Layer Population concentration degree (people per square Negative 9.09% >300 200–300 120–200 5–120 <5 kilometer) D Economic development level (ten-thousand Yuan Positive 9.09% <1 1–2 2–4.5 4.5–8 >8 per person) Reduction of construction P land area per RMB 10,000 of Positive 4.55% <16 16–18 18–20 20–22 >22 GDP (%) Ecological redline rate (%) Positive 18.18% <10 10–20 20–30 30–40 >40 Cultivated land safety Negative 4.55% >1.3 1.1–1.3 1–1.1 0.9–1 <0.9 S and I index Eco-environmental quality Positive 18.18% <20 20–35 35–55 55–75 >75 index Forest coverage rate (%) Positive 18.18% <10 10–20 20–35 35–45 >45 R Soil erosion control rate (%) Positive 18.18% <65 65–75 75–85 85–95 >95 Sustainability 2018, 10, 1728 7 of 20

Table 4. The environmental air quality warning weight setting and index grading.

Standard Index Layer Attribute Weight Red Orange Yellow Green Blue Layer Population concentration degree (people per square Negative 7.69% >300 200–300 120–200 5–120 <5 kilometer) D Economic development level (ten-thousand Yuan Positive 7.69% <1 1–2 2–4.5 4.5–8 >8 per person) Industrial exhaust emissions per capita P Negative 15.38% >2 1.5–2 1–1.5 0.5–1 <0.5 (ten-thousand cubic meters per person) Percentage of days per year with good air quality in Positive 15.38% <50 50–60 60–70 70–80 >80 cities (%) S and I Percentage of days per year with severe air pollution in Negative 15.38% >15 10–15 5–10 2–5 <2 cities (%) Environmental Less General More management Positive 15.38% Unsound Sound sound sound sound system soundness R Environmental risk system Less General More Positive 7.69% Imperfect Perfect perfection perfect perfect perfect Environmental pollution Positive 15.38% >5 4–5 3–4 2–3 <2 loss rate (%)

Table 5. The environmental water quality warning weight setting and index grading.

Standard Index Layer Attribute Weight Red Orange Yellow Green Blue Layer Population concentration degree (people per square Negative 7.69% >300 200–300 120–200 5–120 <5 kilometer) D Economic development level (ten-thousand Yuan Positive 7.69% <1 1–2 2–4.5 4.5–8 >8 per person) Sewage discharge per unit 5000– 1000– P area (tons per square Negative 15.38% >10,000 100–1000 <100 10,000 5000 kilometer) Centralized drinking water sources quality compliance Positive 15.38% <85 85–90 90–95 95–100 100 S and I rate (%) Water functional area Positive 15.38% <65 65–80 80–90 90–100 100 compliance rate (%) Environmental Less General More management system Positive 15.38% Unsound Sound sound sound sound soundness R Environmental risk system Less General More Positive 7.69% Imperfect Perfect perfection perfect perfect perfect Environmental pollution Negative 15.38% >5 4–5 3–4 2–3 <2 loss rate (%) Sustainability 2018, 10, 1728 8 of 20

Table 6. The environmental soil quality warning weight setting and index grading.

Standard Index Layer Attribute Weight Red Orange Yellow Green Blue Layer Population Concentration degree Negative 7.69% >300 200–300 120–200 5–120 <5 (people per D square kilometer) Economic development level Positive 7.69% <1 1–2 2–4.5 4.5–8 >8 (ten-thousand Yuan per person) P Fertilizer utilization rate (%) Positive 15.38% <25 25–30 30–35 35–40 >40 Cultivated land soil quality Positive 15.38% <80 80–85 85–90 90–95 >95 compliance rate (%) S and I Contaminated land safe Positive 15.38% <80 80–85 85–90 90–95 >95 utilization rate (%) Environmental management Less General More Positive 15.38% Unsound Sound system soundness sound sound sound Environmental risk Less General More R Positive 7.69% Imperfect Perfect system perfection perfect perfect perfect Environmental pollution Negative 15.38% >5 4–5 3–4 2–3 <2 loss rate (%)

Table 7. The environmental water resources warning weight setting and index grading.

Standard Index Layer Attribute Weight Red Orange Yellow Green Blue Layer Population concentration degree (people per square Negative 5.88% >300 200–300 120–200 5–120 <5 kilometer) D Economic development level (yen-thousand Yuan Positive 5.88% <1 1–2 2–4.5 4.5–8 >8 per person) Water consumption per RMB 10,000 of GDP (tons Negative 11.76% >200 100–200 50–100 30–50 <30 per ten thousand Yuan) P Water consumption per RMB 10,000 of industrial Negative 11.76% >80 60–80 40–60 20–40 <20 added value (cubic meters per ten thousand Yuan) Water resources per capita 500– 2000– 5000– Positive 11.76% <500 >10,000 (cubic meters per person) 2000 5000 10,000 Water supply in Ecological S and I environment (billion cubic Positive 11.76% <10 10–20 20–30 30–40 >40 meters) Groundwater Negative 11.76% >30 20–30 10–20 0–10 0 over-exploitation rate (%) Effective utilization coefﬁcient of farmland Positive 5.88% <0.3 0.3–0.4 0.4–0.5 0.5–0.6 >0.6 irrigation water R Sewage centralized Positive 11.76% <65 65–75 75–85 85–95 >95 treatment rate (%) Recycled water utilization Positive 11.76% <15 15–20 20–25 25–30 >30 rate (%) Sustainability 2018, 10, 1728 9 of 20

2.5. Single Index Evaluation Because different dimensions of early warning indicators, if not unified, directly affect the specific calculation results, it is necessary to eliminate the dimensions of the original data and convert them into comparable data sequences. The normalized data remove the data limitation and convert them into dimensionless numbers that are allowed for comparison and weighting across different units or orders of magnitude. In this research, we used standard deviation to standardize the dimensions and the deviation standardization, also called 0–1 standardization, is a linear transformation of the raw data. The transfer functions are as follows [52]: X − min(X) Y = (3) max(X) − min(X) max(X) − X Y = (4) max(X) − min(X) where max (X) is the maximum value of the grading standard and min (X) is the minimum grading standard. For a positive index, Formula (3) was used for calculation. For the negative index, Formula (4) was used for calculation. Then, the research adopted a modified deviation standardization to further the standardization. The specific operations are as follows: after standardization of dispersion, the value of X is enlarged 10 times. If the positive index is more than the maximum limit, then it is 10; if it is less than the minimum limit, then it is 0. If the negative index is more than the maximum limit, then it is 0; if it is less than the minimum limit, then it is 10. Finally, the radar map is used to characterize the environment warning to show changes of the indicators and their good or bad trends.

2.6. Integrated Index Evaluation The method of data standardization in the integrated index method is roughly the same as that of the single index method. It adopts standardization of dispersion (0–1 standardization). Then, the research adopts modified deviation standardization for further standardization. The specific operations are as follows: after standardization of dispersion, the value of X is enlarged 100 times. If the positive index is more than the maximum limit, then it is 100; if it is less than the minimum limit, then it is 0. If the negative index is more than the maximum limit, then it is 0; if it is less than the minimum limit, then it is 100. Finally, the weighted summation method was used to summarize the data and results. According to the relative importance of each indicator, we gave a weight coefficient, so that the importance of different evaluation indicators becomes roughly the same and then we accumulated their evaluation results to obtain a total score. The formula is as follows:

B = ∑(Xi × Wi) (5) where B is the integrated index obtained, Xi is the normalized revised value of the ith index data, and Wi is the weight of the ith index [60]. After getting the integrated index, we could get the warning level according to Table8.

Table 8. The integrated score early warning form.

Warning Red Orange Yellow Green Blue Score <20 20–40 40–60 60–80 >80 Sustainability 2018, 10, x FOR PEER REVIEW 9 of 19 minimum limit, then it is 0. If the negative index is more than the maximum limit, then it is 0; if it is less than the minimum limit, then it is 100. Finally, the weighted summation method was used to summarize the data and results. According to the relative importance of each indicator, we gave a weight coefficient, so that the importance of different evaluation indicators becomes roughly the same and then we accumulated their evaluation results to obtain a total score. The formula is as follows:

B = (X × W) (5) where B is the integrated index obtained, Xi is the normalized revised value of the ith index data, and Wi is the weight of the ith index [60]. After getting the integrated index, we could get the warning level according to Table 8.

Table 8. The integrated score early warning form.

Warning Red Orange Yellow Green Blue Sustainability 2018, 10, 1728 10 of 20 Score <20 20–40 40–60 60–80 >80

3. Model Application Application—A—A Case Study of Tianjin City in 20152015

3.1. An Introduction to Tianjin City Tianjin liesliesbetween between the the latitudes latitudes of 38 of degrees 38 degrees 34 min 34 and min 40 and degrees 40 degrees 15 min north15 min and north between and betweenthe longitudes the longitudes of 116 degrees of 116 degrees 43 min and43 min 118 and degrees 118 degrees 4 min east.4 min Additionally, east. Additionally, it is 189 it is km 189 from km fromnorth north to south to and south 117 and km 117 from km east from to west.east to It covers west. It 11,917 covers square 11,917 kilometers. square kilometers. Facing the Facing outside the of outsideNortheast of Asia,Northeast it has Asia great, inﬂuenceit has great on influence north China, on andnorth the China, northeast and andthe northwestnortheast and provinces. northwest It is provinces.located in theIt is northern located partin the of northern the North part China of the Plain, North bordering China thePlain, Bohai bordering Sea to thethe east Bohai and Sea Yanshan to the eastto the and north, Yanshan in the to lower the north, reaches in the of the lower Haihe reaches River of and the across Haihe bothRiver banks and across of the both Haihe banks River. of Itthe is Haihean important River. It functional is an important area for functional water and area soil for conservation, water and soil which conservation, focuses on which the people, focuses habitat, on the peopleecological, habitat security, ecological protection, security and marine protection ecological, and protection. marine Tianjin’s ecological geographical protection. location Tianjin is’s geographicalshown in Figure location2. is shown in Figure 2.

Figure 2. The geographical location of Tianjin.

3.2. Environment Situation in Tianjin 3.2. Environment Situation in Tianjin Although positive progress has been made in the protection of the atmospheric environment in Although positive progress has been made in the protection of the atmospheric environment Tianjin, the coal-dominated energy structure has resulted in a high total amount of air pollutant in Tianjin, the coal-dominated energy structure has resulted in a high total amount of air pollutant emissions. The regional air pollution with PM2.5 and O3 as major pollutants has been prominent. Motor vehicle exhaust gas, volatile organic compounds, and other pollution were still serious, the pollution load was high, the energy structure was not reasonable and it was affected by unfavorable weather conditions and ﬁeld transmission, resulting in the PM10, PM2.5, and other major pollutants being higher than the standards. Tianjin was one of the cities that had the least water resources per capita in the country. Water resources were still the key constraint to the economic and social development in Tianjin. At the same time, the state of the water environment pollution in Tianjin was serious. There was a shortage of water for ecological use, lack of water for entry, poor water quality in the upper reaches, prominent contradictions in the cross-border river pollution, sluggish utilization of sludge disposal, low reclaimed water utilization facilities, and little infrastructural construction in rural areas, which resulted in the overall poor quality of the water environment. Soil types in Tianjin were divided into the mountainous brown soil, cinnamon soil, alluvial soil, swamp soil, and coastal saline soil. Swamp soil was most widely distributed in Tianjin and the soil Sustainability 2018, 10, x FOR PEER REVIEW 10 of 19 emissions. The regional air pollution with PM2.5 and O3 as major pollutants has been prominent. Motor vehicle exhaust gas, volatile organic compounds, and other pollution were still serious, the pollution load was high, the energy structure was not reasonable and it was affected by unfavorable weather conditions and field transmission, resulting in the PM10, PM2.5, and other major pollutants being higher than the standards. Tianjin was one of the cities that had the least water resources per capita in the country. Water resources were still the key constraint to the economic and social development in Tianjin. At the same time, the state of the water environment pollution in Tianjin was serious. There was a shortage of water for ecological use, lack of water for entry, poor water quality in the upper reaches, prominent contradictions in the cross-border river pollution, sluggish utilization of sludge disposal, low reclaimed water utilization facilities, and little infrastructural construction in rural areas, which resulted in the overall poor quality of the water environment. Soil types in Tianjin were divided into the mountainous brown soil, cinnamon soil, alluvial soil, swampSustainability soil, and2018 c,oastal10, 1728 saline soil. Swamp soil was most widely distributed in Tianjin and11 ofthe 20 soil fertility was at a lower level. In general, the quality of the soil environment in Tianjin was in a good state,fertility with only was ata few a lower pollutants level. In general,exceeding the the quality standard of the soilin some environment areas. Most in Tianjin of the was polluted in a good areas werestate, concentrated with only in a fewthe pollutantsperiphery exceeding of the central the standard urban inarea, some which areas. overlap Most ofped the with polluted the areasirrigated areas.were Cadmium concentrated pollution in the in periphery the irrigated of the areas central wa urbans relatively area, which heavy overlapped and the organic with the pollution irrigated was dominatedareas. Cadmium by HCHs pollution and DDTs. in the irrigated areas was relatively heavy and the organic pollution was dominatedAll of the by above HCHs data and DDTs. came from the Tianjin Statistical Yearbook in 2015 [61]; the Tianjin EnvironmentalAll of theStatement above data in 2015 came [62]; from the the Tianjin Tianjin W Statisticalater Development Yearbook inStatistical 2015 [61 ];Bulletin the Tianjin in 2015 [63]; Environmentalthe Tianjin W Statementater Resources in 2015 B [ulletin62]; the Tianjinin 2015 Water [64]; Developmentand the National Statistical Environmental Bulletin in 2015 Protection [63]; the Tianjin Water Resources Bulletin in 2015 [64]; and the National Environmental Protection Plan for Plan for the Thirteenth Five-year [43]. the Thirteenth Five-year [43].

4. Results4. Results AfterAfter calculation, calculation, the the environmental environmental warning radar radar diagram diagram of Tianjinof Tianjin City City in 2015 in was2015 drawn was drawn by by thethe single single index index method method,, as as shown shown in in Figures Figures3–7 .3–7.

FigureFigure 3. The 3. The environmenta environmentall ecology ecology warning warning radarradar map map of of Tianjin Tianjin in 2015.in 2015. Sustainability 2018, 10, 1728 12 of 20 Sustainability 2018, 10, x FOR PEER REVIEW 11 of 19

FigureFigure 4. The 4. The environmental environmental air air quality quality warning radarradar map map of of Tianjin Tianjin in 2015.in 2015.

FigureFigure 5. The 5. The environmental environmental water water quality quality warning radar radar map map of of Tianjin Tianjin in 2015.in 2015.

Sustainability 2018, 10, 1728 13 of 20 Sustainability 2018,, 10,, xx FORFOR PEERPEER REVIEREVIEW 12 of 19

FigureFigure 6.. The 6. The environmental environmental soil soil quality quality wa warningrning radar radar map map of of Tianjin Tianjin in 2015.in 2015.

FigureFigure 7.. The 7. The environmental environmental water water resources resources warningwarning radar radar map map of of Tianjin Tianjin in 2015. in 2015.

In theIn thefigures, ﬁgures, it can it can be be found found that that the the population population concentrationconcentration degree degree in in Tianjin Tianjin was wa muchs much higherhigher than than the thenational national average. average. Excessive Excessive population population hashas alreadyalready restricted restricted the the development development of of TianjinTianjin’s’s environment. environment. At Atthe the same same time, time, Tianjin Tianjin ha hadd aa highhigh level level of of economic economic development, development which,, which couldcould promote promote the thedevelopment development of of environmental environmental technology. On On the the other other hand, hand, it also it also brought brought greatergreater pressures pressures on onthe the environment. environment. Additionally, the industrial exhaust emissions per capita was up to 54,000 standard cubic meters per person and the sewage discharge per unit area was up to 78,547.47 tons per square kilometer. The reason for the high figures is that Tianjin was a century-old heavy industrial city along the coast. Therefore, the air, water, and soil conditions in Tianjin were poorer, especially since the percentage of days per year with good air quality in cities was only 60.3% and the water functional area compliance rate was only 15.4%, which were far below the relevant world and Chinese standards. All of these reflected that,, in 2015, the compound air pollution in Tianjin was Sustainability 2018, 10, 1728 14 of 20

Additionally, the industrial exhaust emissions per capita was up to 54,000 standard cubic meters per person and the sewage discharge per unit area was up to 78,547.47 tons per square kilometer. The reason for the high figures is that Tianjin was a century-old heavy industrial city along the coast. Therefore, the air, water, and soil conditions in Tianjin were poorer, especially since the percentage of days per year with good air quality in cities was only 60.3% and the water functional area compliance rate was only 15.4%, which were far below the relevant world and Chinese standards. All of these reflected that, in 2015, the compound air pollution in Tianjin was prominent and the industrial air pollutants dominated the air; the water pollution state in Tianjin was severe and the aquatic ecosystem was deteriorated; the accumulated soil pollution and organic pollution caused by sewage irrigation were both serious. Moreover, in terms of the system and measures, the environmental management system soundness and the environmental risk system perfection were less than perfect. In general, with significant differences, the development of the various early warning indicators was not balanced. As for water resources, the indicators were extremely uneven. The water resources per capita was only 124.84 cubic meters per person and the water supply in the ecological environment was 3.99 billion cubic meters. It could be seen that Tianjin’s water resources were extremely scarce, far below the world average. Fortunately, the effective utilization coefficient of the farmland irrigation water, sewage centralized treatment rate, and recycled water utilization rate were high enough, which reflected the high degree of water resource utilization in Tianjin. Therefore, although Tianjin’s water resources were extremely scarce, the lives of local residents had not been particularly affected. According to the weighted summation method, the environmental ecology warning integrated index of Tianjin in 2015 was 32.66/100 and the warning level was orange; the environmental air quality warning integrated index of Tianjin in 2015 was 44.59/100 and the warning level was yellow; the environmental water quality warning integrated index of Tianjin in 2015 was 45.37/100 and the warning level was yellow; the environmental soil quality warning integrated index of Tianjin in 2015 was 36.34/100 and the warning level was orange; and the environmental water resources warning integrated index of Tianjin in 2015 was 66.14/100 and the warning level was green. The results showed that, in 2015, the warning integrated index of ecology, air quality, water quality, soil quality, and water resources of Tianjin were all lower and the soil quality warning integrated index was lower than other warnings. The reason for this was that, for a long time, due to the hidden and irreversible nature of soil pollution, Tianjin’s attention to soil pollution was far lower than other pollutions. This phenomenon has changed since the State Council issued a notice of the action plan for the prevention and control of soil pollution in 2016. It was worth noting that the ecology warning integrated index was lowest. In fact, the lowest index could be attributed to the congenitally deficient natural endowments, the unfavorable hydrological conditions, the reduced regional ecological water volume, and the intensity of the regional development, which further endangered ecological security. In addition, although the water resources in Tianjin were very scarce, the environmental water resources warning integrated index was the highest in all the results. This was because, when using the integrated index method, some indicators were concealed by other indicators, for example, the water resources per capita was concealed by the water consumption per RMB 10,000 of GDP. The evaluation results of the single index method and integrated index method all indicated that the ecological environment in Tianjin was facing more pressure and the air, water, soil and ecosystems were in a worse state. Although human beings had taken some measures to respond to the pressure and state in the region, their effect did not satisfy us.

5. Discussion (1) Construction of index system: The research used the DPSIR model to construct the index system. Although it can reflect the relationship between human society and the environment, it was also a little unscientific and unreasonable. The linear causality in the DPSIR model oversimplified the actual situation and only represented the traditional “respond” concept of environmental protection. Sustainability 2018, 10, 1728 15 of 20

(2) Weight determination: The Analytic Hierarchy Process (AHP) method was used to determine the weights. Although it is practical and requires less quantitative data information, which is greatly convenient for our utilization, the Analytic Hierarchy Process (AHP) method has obvious deficiencies, which affected the evaluation results. First, the quantitative data are few and the qualitative components are numerous, so it is not convincing. Second, the large data statistics may make it difficult to determine the weights. In the next study, the Analytic Hierarchy Process (AHP) method should be combined with other methods to make the evaluation result more objective. (3) The single and integrated index evaluation: To get more accurate results, this study used two methods to complement each other in the evaluation. The advantage of the single index method is that it can intuitively show early warning of a specific indicator. The advantage of the integrated index method is that it can analyze the overall situation of the region. However, the single index does not reflect the general trend of early warning in the region and the integrated index method sometimes is too one-sided to cover some of the serious indicators. (4) A case study of Tianjin has proven that the index system and evaluation methods used in this article are appropriate and that it can be applied to other provinces and cities. In turn, the methods proposed in this paper also give us a deeper understanding of the environmental situation in Tianjin. (5) Due to the lack of data, we made an empirical analysis of Tianjin in 2015. Compared to other studies, it may seem to lack a convincing basis. In view of this defect, first, we should add the data of Tianjin in other years or data of other cities in 2015; and second, we have to reduce the uncertainty in constructing the index system. (6) Compared to other studies, this research put together carrying capacity, risk, and ecology warning, which can assess the environmental state in a certain place synthetically. It also combined the air, water, and soil elements to assess the full-scale warning.

6. Conclusions The goal of this study was a methodological literature review of the environmental warning to improve the effectiveness and practicality of environmental warning in cities. This research was necessary to enhance the accuracy of environmental warnings. The following changes were made:

(1) The index system in this paper includes ecological protection, environmental quality (air, water, and soil) and water resources as three parts. All data are publicly available. We distinguished five classes, varying from the Driving forces (D) to the Responses (R), which can not only reflect the environmental state, but can also show the impact and responses of human beings. (2) In this research, some new indicators were used, such as the population concentration degree and economic development level, which more accurately clarified the population and economy. In addition, two qualitative indicators (environmental management system soundness and environmental risk system perfection) made the index system more objective. (3) The Analytic Hierarchy Process (AHP) method was chosen to determine the weights for the 28 indicators of the index system. The single index evaluation and the integrated index evaluation complemented each other to make the warning evaluation objective. Moreover, readers can understand the changes in the indicators and their good or bad trends by radar map. (4) We applied this new method to Tianjin in 2015. The results were in accordance with the environmental conditions in that year. We could consider that we have achieved our purpose of creating new methods. (5) Environmental management should be focused on to enhance the quality of the environment; for example, constructing ecological corridors and biodiversity conservation networks; implementing ecological protection and restoration projects of “mountain, water, forest, land, and lake”; strictly controlling project entry; establishing control lines of development and utilization to control the total amount of water; and speeding up enterprises to carry out Sustainability 2018, 10, 1728 16 of 20

water-saving transformation to effectively reduce industrial production of water consumption and sewage discharge. (6) By a series of analyses, we could draw a conclusion: The method in this research made up for the shortcomings of the previous method. With the advantages of being concise and thorough, it combines the three aspects of the environment, ecology, and resources, especially in the water aspect which has three kinds of attributes. Besides these, it also considers air, water, and soil as the three environmental elements while most studies have not focused on soil. Overall, this paper put forward a successful method in environmental warning and environmental assessment that can be applied in cities and countries.

Author Contributions: W.W. analyzed data formally, proposed the research, conducted fieldwork, and drafted the original manuscript. Y.S. provided methodology. J.W. supervised the overall research project, acquired funding to support this research, and significantly contributed to the editing of the manuscript. Acknowledgments: This research was supported by the National Natural Science Foundation of China (Grant numbers 41401658), and Strategic Environmental Assessment Research Center, Nankai University. We thank Azul Alysum, editor of MDPI, for editing the English text of a draft of this manuscript. Conflicts of Interest: The authors declare no conflicts of interest.

Appendix

Table A1. The calculation method of each indicator.

Indicator Calculation Method

Population density = Total population Population concentration degree Total land area Population concentration degree = Population density × d Economic development level Economic development level = Per capita GDP × k Reduction of construction land area per RMB 10,000 of GDP = Industrial exhaust emissions Industrial exhaust emissions per capita Industrial exhaust emissions per capita Total population of the region Sewage discharge per unit area = Sewage discharge per unit area (Domestic sewage discharge + Industrial sewage discharge + Other sewage discharge) Total areas of the region Fertilizer utilization rate = Fertilizer utilization rate Nutrient components absorbed by plants × Fertilizing amount 100% Water consumption per RMB 10,000 of GDP = Total water consumption Water consumption per RMB 10, 000 of GDP Gross Domestic Product Water consumption per RMB 10,000 of Water consumption per RMB 10, 000 of industrial added value = industrial added value Total water consumption Industrial added value Ecological redline rate Proportion of Ecological redline area × Ecological redline rate= The total land area 100% = Actual area of cultivated land Cultivated land safety index Cultivated land safety index Redline area of cultivated land Eco-environmental quality index

Percentage of days per year with good air Percentage of days per year with good air quality in cities = Number of days per year with good air quality in cities × quality in cities Effective days of monitoring per year 100% Percentage of days per year with severe air Percentage of days per year with severe air pollution in cities = Number of days per year with severe air pollution in cities × pollution in cities Effective days of monitoring per year 100% Centralized drinking water source quality Centralized drinking water sources quality compliance rate = compliance rate Water sources up to standard × Total water source 100% Water functional area compliance rate = Water functional area compliance rate River/Lake/Reservoir water quality compliance × Total monitoring amount of river/lake/reservoir 100% Sustainability 2018, 10, 1728 17 of 20

Table A1. Cont.

Indicator Calculation Method Cultivated land soil quality compliance rate = Cultivated land soil quality compliance rate Area of cultivated land up to standard × Total area of cultivated land 100% Contaminated land safe utilization rate = Contaminated land safe utilization rate Area of safe utilization of contaminated land × Total area of contaminated land 100% = Total amount of water resources in the region Water resources per capita Water resources per capita Total population in the region Water supply in ecological environment Data is directly available Groundwater over − exploitation rate = Groundwater over-exploitation rate − Over exploitation of groundwater amount × Total recoverable groundwater 100% = Forest cover area in the region × Forest coverage rate Forest coverage rate Total area in the region 100% Soil erosion control rate = Soil erosion control rate Total amount of soil erosion after government × Total amount of soil erosion before government 100% Environmental management system Qualitative indicator soundness Environmental risk system perfection Qualitative indicator Environmental pollution loss rate = Environmental pollution loss rate Amount of environmental pollution loss in the region × Total amount of GDP in the region 100% Effective utilization coefﬁcient of farmland Effective utilization coefﬁcient of farmland irrigation water = Net water used by crops during the period of irrigation irrigation water Total water intake from irrigation canal Sewage centralized treatment rate = Sewage centralized treatment rate Amount of sewage treated by sewage treatment plant × Total amount of urban sewage discharge 100% Recycled water utilization rate = Recycled water utilization rate Amount of recycled water utilization × Total amount of sewage treatment 100%

Remark: (1) d is the weight coefﬁcient of the population growth rate, and the values of d are shown in Table A2.

Table A2. The values of d.

Population Growth Rate <0 0–0.005 0.005–0.01 0.01–0.015 >0.015 Value of d 0.8 1.2 1.4 1.6 1.8

(2) k is the weight coefﬁcient of Per capita GDP growth rate, and the values of k are shown in Table A3.

Table A3. The values of k.

Per Capita GDP Growth Rate <5% 5–10% 10–20% 20–30% >30% Value of k 1 1.2 1.3 1.4 1.5

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